Florence AI Navigator

Comprehensive Sales Manual

Version 3.0 — February 2026
NightingaleMD Sales Enablement

Confidential & Proprietary. This document is intended solely for NightingaleMD sales representatives and authorized personnel. All patient data shown in screenshots is simulated demo data and does not represent actual patients. All statistics cited herein are based on internal pilot program data and are subject to change. This product is not a medical device and does not provide clinical diagnoses.

Table of Contents

Part 1: Strategic Context & Value Proposition

Chapter 1: Introduction

Audience: This manual is designed for sales representatives at NightingaleMD. It provides the strategic context, workflow knowledge, and demo scripts needed to effectively showcase the Florence AI Navigator to prospective clients, including clinical stakeholders (CMOs, quality directors) and practice managers.

Purpose: The primary purpose of this manual is to serve as a comprehensive guide for conducting live client demos. It will equip you with the knowledge to not only demonstrate the features of Florence but also to articulate its profound value proposition within the complex ecosystem of Comprehensive Care Assessment (CCA).

Key Performance Indicators

*These metrics are based on NightingaleMD's internal pilot program conducted in Q3 2025 with a sample of 12 participating practices. Results may vary based on practice size, patient population, and implementation approach. Full methodology available upon request.

Chapter 2: The Traditional CCA Process (Before Florence)

The traditional Comprehensive Care Assessment (CCA) process is a manual, time-consuming, and often inefficient workflow that places a heavy burden on care navigators and providers. Understanding these pain points is critical to articulating the value of Florence.

The Manual CCA Workflow

1. Manual Data Review: The care navigator manually reviews data from the Care Opportunities and Outcomes Platform (COOP) to identify patients due for a CCA (e.g., recently discharged, due for an AWV).
2. Manual Chart Review: The navigator manually reviews the patient's chart in the EHR to identify all potential care gaps, including suspect diagnoses, quality measures, and frailty indicators.
3. Manual Patient Outreach: The navigator manually calls the patient to schedule a Transitional Care Management (TCM) call and a follow-up appointment.
4. Manual Documentation Preparation: Before the appointment, the navigator manually prepares all necessary documentation, including a summary of care gaps and supporting evidence.
5. Provider Encounter: During the visit, the provider must manually review the patient's chart and the navigator's notes to address care gaps, often without real-time decision support.
6. Manual Follow-up: After the visit, the navigator manually coordinates any necessary follow-up, such as specialist referrals or patient education.

Key Pain Points

Chapter 3: The CCA Lifecycle with Florence

Florence transforms the CCA process by automating and enhancing each phase of the lifecycle, from trigger to ongoing management. This integrated approach ensures a seamless, efficient, and effective workflow across all five phases.

Phase 1: Trigger

Florence automatically detects CCA triggers from COOP in real-time, including hospital discharge notifications, Annual Wellness Visit (AWV) due dates, new quality measure gaps, and suspect diagnosis gaps. When a trigger is detected, Florence immediately begins compiling the patient's clinical profile and initiating the pre-encounter workflow. In the demo, Jane Doe's discharge from St. Joseph's Hospital triggered Florence to begin the entire CCA process automatically.

Phase 2: Pre-Encounter (Engage)

Once a trigger is detected, Florence initiates the pre-encounter workflow. This includes compiling all necessary CCA components from COOP and the EHR, automatically scheduling and conducting the TCM outreach call using the Engage workflow, confirming the follow-up appointment with the patient, and staging all identified care gaps for provider review. The Engage workflow uses AI-powered voice to conduct natural, empathetic conversations with patients, handling medication verification, appointment scheduling, and symptom screening.

Phase 3: Encounter

During the patient visit, Florence acts as a real-time copilot for the provider. The Nightingale Navigator sidebar displays all staged gaps with supporting evidence directly within athenaOne. The provider can accept, reject, or defer each gap with a single click, and Florence auto-generates MEAT-criteria documentation in real-time as gaps are accepted. This eliminates the documentation burden and ensures compliance.

Phase 4: Post-Encounter (Convene)

After the visit, Florence automates the post-encounter workflow. This includes coordinating specialist referrals and follow-up appointments, sending automated patient education materials, and using the Convene workflow to facilitate care team meetings. Convene enables three-way calls between the patient, provider, and specialists, with real-time transcription and documentation. The File to EHR function uses generative browsing to securely file all documentation to athenaOne with a single click.

Phase 5: Ongoing Chronic Condition Management (Check-In)

Florence provides ongoing support for patients with chronic conditions using the Check-In workflow. This SMS-based monitoring system conducts routine check-ins, tracks medication adherence and care plan progress, monitors symptoms, and escalates to a human navigator when necessary. For Jane Doe, this means daily post-discharge monitoring to prevent readmission and ensure recovery compliance.

Part 2: The Pre-Encounter Workflow & Demo Scripts

Chapter 4: The Navigator's View — Automating Pre-Encounter Tasks

This chapter details the pre-encounter workflow from the care navigator's perspective. The goal is to demonstrate how Florence automates the most time-consuming manual tasks, allowing navigators to operate at the top of their license.

When you first open the Florence AI Navigator, you see the side-by-side view: the athenaOne EHR on the left and the Florence Copilot sidebar on the right. The patient's chart is already loaded with all relevant clinical data, including the HPI, vitals, screenings, problem list, and medications.

Figure 1: The Florence AI Navigator integrated into athenaOne. The left panel displays the patient's EHR chart (Subjective, Objective, Problem List), while the right panel shows the Nightingale Navigator sidebar with patient summary, workflow buttons (Engage, Convene, Check-In), and Care & Diagnosis Gaps.

The Florence Copilot sidebar immediately shows the patient's key information at a glance. Jane Doe is flagged as High Risk and enrolled in CCM (Chronic Care Management). The three workflow buttons — Engage, Convene, and Check-In — are prominently displayed. Below the buttons, the Florence Summary dropdown provides a quick clinical overview, and the Care & Diagnosis Gaps section shows all 9 identified gaps.

Figure 2: The Florence Copilot sidebar showing patient summary (Jane Doe, 68 y/o F, High Risk, CCM, MRN: 202070), Sync and Post-Visit action buttons, workflow buttons (Engage, Convene, Check-In), Florence Summary dropdown, and the first two of 9 Care & Diagnosis Gaps with category filters.

The Care & Diagnosis Gaps section shows all 9 gaps that Florence has automatically identified from COOP. The gaps are organized by category using filter buttons: All (9), Recapture (0), Suspect (4), Quality (3), and Frailty (2). The initial view shows the first two gaps; scrolling reveals additional gaps including Type 2 Diabetes with Hyperglycemia, Colorectal Cancer Screening, Statin Therapy, Nephrology Referral, Fall Risk Assessment, Comprehensive Frailty Assessment, and Morbid Obesity.

Figure 3: The initial Care & Diagnosis Gaps view showing the first two of 9 identified gaps: Chronic Kidney Disease Stage 3a (Suspect, COOP, High — ICD-10: N18.31, HCC 138) and Major Depressive Disorder (Suspect, COOP, High — ICD-10: F33.1, HCC 59). Each gap includes a "Stage for MD Review" button and a "Details" expander.

Figure 4: Scrolling the gaps list reveals additional gaps, including Type 2 Diabetes with Hyperglycemia (Suspect, ICD-10: E11.65, HCC 19), Colorectal Cancer Screening (Quality), and Statin Therapy for Cardiovascular Disease (Quality). The "Future Visit" button appears on gaps that can be deferred.

Clicking the Details button on any gap reveals comprehensive information including the full ICD-10 description, supporting evidence from the patient's chart, and the clinical rationale for the gap identification. This level of detail is what enables providers to make informed decisions at the point of care.

Figure 5: Expanded details for the Chronic Kidney Disease Stage 3a suspect gap, showing the full ICD-10 description ("Chronic kidney disease, stage 3a. Stage 3a is defined as eGFR 45–59 mL/min/1.73m²"), supporting evidence from the chart (eGFR: 52 mL/min/1.73m², Creatinine: 1.4 mg/dL), and the "Stage for MD Review" action button.

Each gap has a "Stage for MD Review" button that the navigator uses to prepare gaps for the provider encounter. The navigator reviews each gap and stages the ones that are relevant for the upcoming visit. Gaps that are not appropriate for the current visit can be deferred using the "Future Visit" button. This targeted staging ensures the provider sees only the most relevant gaps during the encounter.

Figure 6: The "Stage for MD Review" buttons visible on each care gap. The navigator can stage individual gaps for the provider encounter or defer them to a future visit. The "Show staged items" checkbox allows the navigator to filter the view to see only staged gaps.

Chapter 5: The Engage Workflow — AI-Powered Patient Outreach

The Engage workflow is Florence's AI-powered voice outreach tool. It automates a wide range of patient communication tasks, from TCM calls to appointment reminders, using natural language processing to have human-like conversations with patients.

Clicking the Engage button initiates the AI-powered TCM outreach call. The button changes to "In Call..." to indicate the call is in progress, as shown in Figure 7. Florence automatically dials the patient and begins the conversation using the appropriate protocol (in this case, a post-discharge TCM call).

Figure 7: The Engage workflow in progress. Note the Engage button now displays "In Call..." status (highlighted in teal), indicating Florence is actively conducting the AI-powered TCM outreach call with the patient. The Convene and Check-In buttons remain available for other workflows.

The Transcript tab shows the real-time conversation between Florence and the patient. Florence initiates the call with a warm, professional greeting and confirms the patient's identity before proceeding with the TCM protocol. The full transcript is automatically saved to the patient's record.

Figure 8: The Engage transcript showing the real-time conversation between Florence and the patient. The sidebar displays the expanded gap details with the full ICD-10 description and supporting evidence, demonstrating how Florence provides clinical context alongside the patient interaction.

Full Engage Workflow Transcript: Jane Doe TCM Call

After the Engage call completes, the Documentation tab shows the auto-generated clinical documentation. Florence automatically creates a structured summary of the call, including key findings, patient responses, and next steps — all formatted to meet MEAT criteria compliance requirements.

Figure 9: The Documentation tab showing Florence's auto-generated clinical documentation from the Engage call, including the call summary, medication verification results, appointment confirmation, and recommended follow-up actions.

Part 3: The Encounter Workflow & Provider Perspective

Chapter 6: The Provider's View — A Seamless Encounter

This chapter focuses on the provider's experience during the patient encounter. The key is to demonstrate how Florence acts as an intelligent copilot, streamlining the provider's workflow and enabling them to focus on patient care, not documentation.

The Provider View displays all staged gaps with expanded clinical information, including the full ICD-10 description and supporting evidence from the chart. The provider can review each gap, accept or reject it, and Florence automatically generates the MEAT-criteria documentation in real-time.

Figure 10: The full dashboard in Provider View, showing the athenaOne EHR on the left with Jane Doe's clinical data (HPI, Vitals, Screenings, Problem List) and the Nightingale Navigator sidebar on the right with staged care gaps and expanded clinical details.

The left panel of the dashboard shows the full athenaOne EHR patient chart, including the Subjective section (HPI, ROS), Objective section (Vitals, Screenings & Findings), Problem List, Medications, Referrals, and more. Florence integrates seamlessly alongside this existing workflow without disrupting the provider's familiar EHR experience.

Chapter 7: Provider Best Practices & Objection Handling

Best Practices for Providers

Trust the Staged Gaps: The care gaps staged by Florence are based on real-time data from COOP, which is the source of truth for gap validation. Providers can trust that these gaps are accurate and up-to-date.

Leverage the Sidebar: The Florence sidebar is designed to be an at-a-glance resource. Providers should use it to quickly review all open gaps and supporting evidence without leaving the patient's chart.

Embrace One-Click Attestation: The one-click MEAT criteria attestation is a powerful time-saving feature. Providers should use it to quickly document their clinical decisions rather than manually typing notes.

Review Auto-Generated Documentation: While Florence's documentation is highly accurate, providers should always give it a quick review before signing the note. This ensures clinical accuracy and maintains the provider's professional responsibility.

Common Objections & Responses

Part 4: Post-Encounter & Ongoing Management

Chapter 8: The Convene Workflow — Care Team Collaboration

The Convene workflow facilitates seamless communication and collaboration among the patient's care team. It allows navigators to quickly schedule and launch three-way calls between the patient, the provider, and any other relevant stakeholders (e.g., specialists, family members).

Clicking the Convene button initiates a three-way call. The button changes to "In Session..." to indicate the call is in progress, as shown in Figure 11. Florence automatically dials the patient first, then connects the care team member.

Figure 11: The Convene workflow in progress. The Convene button now displays "In Session..." status, indicating Florence is facilitating the three-way call between the patient, care manager, and provider. The Engage button remains available for separate outreach.

Chapter 9: The Check-In Workflow — Proactive Patient Monitoring

The Check-In workflow is Florence's automated patient monitoring tool. It uses SMS to proactively check in with patients, track their progress, and identify potential issues before they become serious.

Clicking the Check-In button initiates the SMS-based patient monitoring workflow. Florence sends personalized messages based on the patient's condition and care plan, and monitors responses for any concerning symptoms that may require escalation.

Figure 12: The Check-In workflow showing the SMS-based patient monitoring interface. Florence sends personalized messages to Jane Doe based on her post-discharge care plan, monitoring symptoms, medication adherence, and recovery progress.

Chapter 10: Filing to the EHR & Conclusion

Closing the Loop

Once the provider has reviewed and accepted the care gaps, Florence makes it easy to file all necessary documentation to the EHR. This is a critical step in closing the loop and ensuring the patient's chart is complete and up-to-date.

The Future of CCA

Florence is more than just a tool; it is a new way of thinking about Comprehensive Care Assessment. By automating the manual, time-consuming tasks that have traditionally burdened care navigators and providers, Florence empowers them to focus on what they do best: providing high-quality, patient-centered care.

*Based on NightingaleMD internal pilot program, Q3 2025. Results may vary. Full methodology available upon request.

Appendices

Appendix A: Screenshot Reference Guide

Appendix B: Quick Reference — Demo Flow Cheat Sheet

For a streamlined 15–20 minute demo, follow this flow:

Total Demo Time: 15–20 minutes

Application URL: https://florence-intel-dashboard.vercel.app

Version 3.0 — February 16, 2026
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